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Overview

The SERF Index

Under the International Covenant for Economic, Social, and Cultural Rights, ICESCR, countries are obligated to devote the maximum of their available resources to progressively realize the substantive rights enumerated in the Covenant. Thus, measuring the extent to which a country fulfills its economic and social rights obligations under the ICESCR requires considering the level of rights enjoyment in the country relative to the level of the country’s obligation. The SERF Index uses socio-economic statistics like school enrollment and child mortality rates to gauge the extent to which rights-holding individuals enjoy economic and social rights. A country’s level of obligation is specified using an innovative approach that maps Achievement Possibility Frontiers, APFs. APFs benchmark each country’s level of obligation by relating countries’ per capita GDPs with countries’ performance on socio-economic statistics reflecting economic and social rights enjoyment. The basic SERF Index methodology rigorously assesses countries’ fulfillment of their obligations with regard to a specific social and economic right as the percentage of the feasible level of economic and social rights enjoyment achieved. Country scores on the resultant component right indices reflecting the different substantive rights are then averaged to yield the composite SERF Index. There are two versions of the SERF Index; the Core SERF Index and the High-Income SERF Index. The Core SERF Index is the most relevant for low- and middle- income countries while the High-Income SERF Index, as its name indicates, is most relevant for high-income countries. Both variants of the SERF Index are computed for all countries with the relevant data. The technical note below describes the construction of both variants of the SERF Index in greater detail.

The 2019 SERF Index Update provides SERF Index scores for 11 separate years; 2006 through 2016, and can be downloaded at the SERF Index data tab. This year’s update replaced some of the indicators measuring rights enjoyment to take advantage of improved data availability and to better reflect some of the sustainable development goals. For example, the gross secondary enrollment rate is replaced with the net secondary enrollment rate, and the percentage of the rural population with an improved water source is replaced by the percentage of the population with access to an improved water source on premises The Core SERF Index covers approximately 80 countries (the exact number depending on the year) and up to 193 countries for the component Right Indices (the exact number depending on the right and the year), and is comparable across the countries and across the 11 years. The High-Income SERF Index covering all five rights can be calculated for 23 countries in 2015 and 2016. Because the Right to Food score is only available for 2015 and 2016, we calculate a High-Income SERF Index variant that excludes the Right to Food. This variant can be calculated for approximately 30 countries (the exact number depending on the year). The High-Income component Right Indices can be calculated for between 35 and 94 countries depending on the right and year. Both variants of the High-Income SERF Index are comparable across the countries and years for which each is available. The series for each year uses the most recently available data for each country as of the specified year when computing the index. However, because the surveys providing many of the indicators are not conducted annually, the data used for each year’s series are not always unique. For example, in the case of the Core Right to Education Index for Benin, the 2014, 2015, and 2016 series use data on the adjusted net primary school enrollment rate in 2014. Because both the Core SERF Index and High-Income SERF Index are calculated for all countries (low- and middle- income as well as high-income countries) with available data, researchers can evaluate countries with the available data on either standard. The full data sets including the individual indicator performance scores as well as the Right Indices are incorporated into the downloadable excel files.

The older SERF Index updates, the 2011 update providing SERF Index scores for 2008, and the 2012 update providing SERF index scores for 2009, the 2013 update providing comparable data covering the 2000 through 2010 period, the 2015 SERF Update providing comparable data for the 2003 to 2012 period and the 2017 SERF Update providing comparable data for 2005 to 2015 are now outdated. However, they have been retained for the convenience of researchers still working with these older data files, and can be downloaded from the “Data Archives” tab by clicking on the 2011 Downloads, the 2012 Downloads the 2013 Downloads the 2015 Downloads and the 2017 Downloads pages, respectively.

SERF Index Historical Trends 1970 – 2010

Have countries progressed or regressed in meeting their commitments to fulfill economic and social rights? The SERF Index has been estimated for countries with internationally comparable data spanning four decades. The Core Historical SERF Index covers all countries except the high income OECD countries. Two variants of the Supplementary Historical SERF index are available, one spanning the four decades and a second incorporating data on the quality of education but only spanning the last two decades because comparable international data on the quality of education are not available for the 1970s and 1980s.

The Core and both variants of the Supplemental Historical SERF Index as well as the component right indices from which they are aggregated can be downloaded through this data portal in both pdf and excel formats.

Due to data limitations, some indicators were substituted in constructing the trend data. A technical note describing how the construction of the SERF Index Historical Trends differs from the International SERF index is available through this portal and should be read in conjunction with the Technical Note on the International SERF Index Methodology above.

Two variants of the Supplementary Historical SERF index are available, one spanning the four decades and a second incorporating data on the quality of education but only spanning the last two decades because comparable international data on the quality of education are not available for the 1970s and 1980s.

The Core and both variants of the Supplemental Historical SERF Index as well as the component right indices from which they are aggregated can be downloaded through this data portal in both pdf and excel formats.

News & Events

The Economic and Social Rights Empowerment Initiative has joined forces with the Human Rights Measurement Initiative, HRMI. HRMI has adopted the SERF Index and underlying metrics as its economic and social rights scores for their “income-adjusted” quality of life metrics. HRMI proides extensive data visualization tools showing country performance over time and comparing country performance […]

Sakiko Fukuda-Parr, Terra Lawson-Remer and Susan Randolph are the 2019 winners of the prestigious Grawemeyer Award for Ideas for improving World Order. The trio received the award for their book Fulfilling Economic and Social Rights. They will travel to Louisville, Kentucky to give a series of lectures on their book and will formally receive the […]

The Human Rights Measurement Initiative, HRMI, has adopted the Right Indices comprising the SERF Index as their economic and social rights metrics. They have just launched data visualization tools that allow you easily to compare a country’s performance on the different rights at a given time and over time, and to compare performance on each […]

The 2017 SERF Index Update covers the years 2005 through 2015. This major update incorporates the construction of updated Achievement Possibility Frontiers using 2011 PPP$ GDP per capita data. Learn more about this update here. Download the 2017 data here

Economic and Social Rights Empowerment Initiative

The Economic and Social Rights Empowerment Initiative was initiated by Sakiko Fukuda-Parr and Terra Lawson-Remer at the New School, and Susan Randolph at the University of Connecticut, and its start-up was supported in part by the National Science Foundation Grant # 1061457.